Investigação Operacional

Base Knowledge

Basic concepts of Algebra.

Teaching Methodologies

A learning strategy based on the experimentation of the subjects exposed in the theoretical class is used:
a) In the theoretical component, an oral presentation of the subjects is made, using the board and projections in Power-Point (the active participation of students is encouraged by asking simple questions) and small demonstrative examples of the taught content are presented.
b) In the theoretical-practical component, the knowledge acquired in the theoretical classes is applied
solving exercises (the exercises sheet are available on the Moodle platform and students must bring them to class).
Individual student study outside of classes is required (for better monitoring of classes).

Learning Results

Goals:

After attending this curricular unit, students must: know and understand the fundamental characteristics of the most representative optimization and decision problems; be able to translate simple optimization and decision problems into mathematical models of linear programming (LP); understand the LP algorithms and know to apply the appropriate ones to solve this kind of problems; be able to interpret the solutions obtained by the application of these algorithms to the mathematical models; and to analyse the sensitivity of this (these) solution(s) to variations in model’s parameters.

The knowledge acquired in this course can be applied in solving similar algorithms/problems in a real context.

Skills:

After attending this course, students must:

– Be able to identify the different types of problems that can be studied with the use of operational research techniques.

– Be able to translate simple optimization and decision problems into mathematical models of linear programming (LP);

– Understand the LP algorithms and know to apply the appropriate ones to solve this kind of problems;

– Be able to interpret the solutions obtained by the application of these algorithms to the mathematical models;

– Be able to analysis the sensitivity of the optimal solution(s) obtained due to variations in model’s parameters.

– Application of the concepts learned in this curricular unit in the resolution of more complex similar problems in a professional context.

Program

Theoretical content:
1 – Introduction to Operations Research
2 – Linear Programming
3 – Introduction to Post-Optimization and Sensitivity Analysis
4 – Multi-Objective Linear Programming
5 – Goal Programming

Theoretical-Practical content:
– Resolution of theoretical-practical exercises involving the various chapters of the theoretical program (exercises sheets available on Moodle).

Curricular Unit Teachers

Ana Rosa Pereira Borges

Grading Methods

Students can choose two different assessment methods:

a) Final Evaluation,

 - Consists of a Final Exam (20 points), covering all the subjects taught.

b) Continuous Assessment (by tests, mandatory minimum of 2/3 classes attendance (T +TP)),

 - Consists of two (2) Evaluation Tests to be carried out during the semester (50%[=10 points] + 50%[=10 points] = 20 points).

 

Comments:

  • The Final Exam and the Evaluation Tests are “closed book” and the use of any equipment during the tests is not authorized.
  • The date and the subject matter covered in the 1st assessment Evaluation Test will be announced to students (with due advance) during classes.
  • The date of 2nd assessment Evaluation Test coincides with the date of the last class of this UC.
  • The 2nd Evaluation Test covers all the subject taught.
  • Mandatory minimum of 35% in each Evaluation Test.
  • Each test will be rated at 20 points, with the continuous assessment final grade being the average of the grades obtained in both evaluation tests.
  • The student must send an email by the end of the 5th week of classes (saturday until 11:55 p.m.) to the teacher responsible for the CU indicating which of the assessment methods he/she wishes to be assessed in for this CU (Continuous Assessment or Final Evaluation). If no email is received, it is assumed that the student is taking the Final Evaluation method.
  • Failure to meet the minimum requirements in any of the tests, withdrawal from any of the tests or failure to obtain a final grade in the final continuous assessment grade greater than or equal to 9.5 points, means that the student has not passed the continuous assessment regime.
  • The student who have taken continuous assessment regime will automatically be prevented from accessing the 1st Call Final Examination, regardless of the grade he or she obtains at the end (positive (Dismissed with success) or negative (Failed));

  • The final exam will always cover the entire subject and cannot be solved in parts.

  • All students with final grades greater than or equal to 9.5 points in the Curricular Unit (whether obtained by continuous assessment or Final Evaluation) may take a mandatory oral exam, if the teacher so understands (which will be scheduled for up to 3 days after the final grade are made known to the students).
    • The oral exam will cover all the subject taught in the Curricular Unit.
    • If the student does not present himself to the oral exam, he will not be approved.

    Internship(s)

    NAO

    Bibliography

    Main Bibliography:

    – Documentation that supports classes (Notes and slides, available in moodle or on the academic management platform).

    – Hillier, F. S., & Lieberman, G. J. (2010). Introduction to Operations Research (6th ed.). New York: McGraw-Hill. [available at ISEC’s Library the 5th edition = Cota ISEC: 3-9-31 (ISEC) – 08145].

    – Clímaco, J. N., Antunes C. H., & Alves M. J. (2003). Programação Linear multiobjectivo: do modelo de programação linear clássico à consideração explícita de várias funções objectivo. Coimbra – Imprensa da Universidade de Coimbra. [Cota ISEC: 3-9-95 (ISEC) – 13356; 3-9-96 (ISEC) – 13392]

    – Ramalhete, M., Guerreiro, J., & Magalhães, A. (1984-1985) Programação Linear (vol. I e vol. II) (6a ed.). Lisboa: McGraw-Hill. [Cota ISEC: 3-9-22 (ISEC) V.1º v. – 05262; 3-9-23 (ISEC) V.2º v. – 07016; …]

    – Hill, M. M.; Santos, M. M. (2009) – Investigação Operacional (vol.I e vol.II) (2th ed.). Lisboa: Edições Sílabo [Cota ISEC: 3-9-111 (ISEC) V.1º v. – 16149 ; 3-9-112 (ISEC) V.2º v. – 15173]

     

    Additional Bibliography:

    – Tavares, L.V., Oliveira, R. C., Themido, I. H., Correia, F.N. (1996) Investigação Operacional. McGraw-Hill.

    – Ravindran, A.; Phillips, D. T.; Solberg, J. J. (1987) Operations Research: Principles and Practice. (2nd ed.). New York: John Wiley [Cota ISEC: 3-9-57 (ISEC) – 09253]

    – Taha, H. A. (2007) Operations research: an introduction (8th ed.). London: Prentice-Hall [available at ISEC’s Library the 5th edition = Cota ISEC: 3-9-29 (ISEC) – 07857]

    – Murthy, P. R. (2007) Operations Research (2nd ed.). New Delhi: New Age International Publishers

    – Bazaraa M.S., Jarvis J.J., & Sherali H.D. (2010) Linear Programming and Network Flows (4th ed.), Wiley

    – Steuer, R. (1986) Multiple Criteria Optimization: theory, computation and application. John Wiley & Sons.